Research

CU �鶹ӰԺ enters next phase to develop national quantum networking capabilities

Charles Ferrer — Thu, 09 Jul 2026 14:36:28 +0000

CU �鶹ӰԺ enters next phase to develop national quantum networking capabilities Charles Ferrer Thu, 07/09/2026 - 08:36

Researchers have advanced to the design phase to build a scalable quantum network capable of transmitting quantum information across long distances at unprecedented rates. The NSF-funded project aims to develop technologies to unlock new capabilities for quantum computing, communications and sensing.

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Scientists harness AI to reveal forces behind glacier surges

Charles Ferrer — Thu, 05 Mar 2026 22:12:42 +0000

Scientists harness AI to reveal forces behind glacier surges Charles Ferrer Thu, 03/05/2026 - 15:12

Charles Ferrer

Ute Herzfeld (PI), Harald Sandal (pilot), Gustav Svanstroem (helicopter technician) and Matthew Lawson (research assistant) during the Negribreen Glacier System Airborne Geophysical campaign (Photo Credit: Thomas Trantow).

Glaciers are constantly changing and reshaping the Earth’s surface.

CU �鶹ӰԺ researchers have developed a new machine learning tool to better understand how Arctic glaciers suddenly accelerate or “surge”.

The team, led by Ute Herzfeld, a research professor in the Department of Electrical, Computer and Energy Engineering, created an open-source cyberinfrastructure called GEOCLASS-image, designed to decode the physical processes behind glacier motion using high-resolution satellite imagery and machine learning.

Glacier surges are sudden bursts of movement in otherwise slow-flowing ice.

Normally, glaciers move at a steady pace, but during a rare “surge”, that rate can accelerate up to 200 times faster than usual. The ice fractures into deep crevasses and pushes large volumes of ice toward the ocean. These dramatic events provide scientists with new insight into the unpredictable drivers of sea-level rise.

“Most deep machine learning systems don’t know what to look for in images,” said Herzfeld, who is also the director of the Geomathematics, Remote Sensing and Cryospheric Sciences Laboratory. “We have built a system that understands the physics of ice deformation, so the classifications actually mean something.”

Understanding how a glacier surges

Unlike traditional artificial intelligence systems that often struggle to interpret complex natural phenomena, the team created a new neural network approach—VarioCNN—to better understand glacial acceleration.

“Surging glaciers are one of the deep uncertainties in sea-level rise projections,” Herzfeld said. “They can move much faster than normal and current earth system models do not yet have the ability to account for them.”

To tackle this problem, Herzfeld and her team merged two powerful approaches: a deep convolutional neural network (CNN), common in the field of computer science and remote sensing and a physics-informed neural network model that captures how crevasses in the ice form, widen and intersect during motion.

“Think of neural networks as Lego blocks,” Herzfeld said. “We’ve taken some from physically informed models, some from deep learning and built a new kind of AI that’s meaningful.”

Putting AI to the test

The team tested their approach on a real-world event: the unexpected 2016 surge of Negribreen, a glacier located in the Arctic archipelago of Svalbard a 1,000 km south of the North Pole.

This isn’t just another AI model but one that understands the physics of glacial acceleration.
~Ute Herzfeld

Using Maxar WorldView satellite imagery collected in 2016-2018, the researchers tracked subtle changes across the glacier’s surface with remarkable detail.

They discovered that crevasse patterns, which change dramatically during a surge, hold information about surge dynamics that can be retrieved using their neural network approach.

One-dimensional crevasses appeared at the leading edge of the surge, while deeper within the surge area, complex patterns tell the story of the transformation and deformation of the ice, which can be of use in numerical modeling of the glacial acceleration.

Shear, a type of deformation that plays a key role in glacial acceleration, is easily misclassified in deep learning, but correctly identified using VarioCNN.

With their new VarioCNN model, they classified different types of crevasses from satellite images and used those patterns to interpret how the glacier moved and changed.

Results of the classification were then used to understand how the surge expanded and affected the entire Negribreen glacier system. Ultimately, ice mass equivalent to 1% of global annual sea-level rise transferred to the ocean.

Published in Remote Sensing, their results demonstrated how integrating physical knowledge into a neural network model, carried out at the computational level, can advance machine learning and glaciological understanding of glacier surges. The paper was selected as the cover story of Remote Sensing receiving record downloads during the first two weeks after publication.

Student Connor Meyers setting up a GPS station at the edge of Negribreen (Photo Credit: Ute Herzfeld).

“The problem of task-oriented machine learning is especially intriguing to me,” said Silas Twickler (Phys’25) who was a research assistant on the project. “While simply applying pre-existing neural networks may be sufficient for certain applications, the augmentation of these networks can allow for a drastic improvement in machine learning.”

AI for the geosciences

A major hurdle in applying machine learning to studying glaciers is the limited amount of labeled data. To overcome this, Herzfeld’s team developed a way that allows scientists to gradually refine the model using a relatively small number of hand-labeled satellite images.

VarioCNN was trained on just a few thousand of examples, far fewer than the 100,000 images than typical deep learning models require. Due to its modular design, the GEOCLASS cyberinfrastructure can be adapted to study other geophysical processes and potentially surfaces of other planets.

“Our tool is not just for glaciologists, but for anyone working with remote sensing and physical systems,” Herzfeld said. “Ultimately, we hope to give scientists better tools to understand how the Earth is changing.”

This research was funded by the National Science Foundation Office of Advanced Cyberinfrastructure and NASA Earth Sciences Division.

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Negribreen glacier during an ice surge in 2017 (Credit: Ute Herzfeld).

Researchers build ultra-efficient optical sensors shrinking light to a chip

Charles Ferrer — Mon, 23 Feb 2026 16:37:42 +0000

Researchers build ultra-efficient optical sensors shrinking light to a chip Charles Ferrer Mon, 02/23/2026 - 09:37

Lu at the new electron beam lithography system used to develop microresonators at COSINC.

Charles Ferrer

Lu at the new electron beam lithography system used to develop microresonators at COSINC.

CU �鶹ӰԺ researchers have built high performing optical microresonators opening the door for new sensor technologies.

At its simplest form, a microresonator is a tiny device that can trap light and build up its intensity.

Once the intensity is high enough, researchers can perform unique light operations.

“Our work is about using less optical power with these resonators for future uses,” said Bright Lu, a fourth-year doctoral student in electrical and computer engineering and a lead author on the study. “One day these microresonators can be adapted for a wide range of sensors from navigation to identifying chemicals.”

For this endeavor published in Applied Physics Letters, the team focused on ‘racetrack’ resonators, named for their elongated shape that resembles a running track.

Specifically, researchers used ‘Euler curves’ — a type of smooth curve also found in road and railway design. Just as cars can’t make sharp right-angle turns in motion, light can not be forced into abrupt bends.

“These racetrack curves minimize bending loss,” said Won Park, Sheppard Professor of Electrical Engineering, a co-advisor on the study. “Our design choice was a key innovation of this project.”

By guiding light smoothly through the resonator, they dramatically reduced light loss, allowing photons to circulate longer and interact more strongly inside the device.

If too much light is lost, Lu says, high light intensities can’t be achieved for these microresonators to operate at the needed performance.

Made in Colorado

Incredibly small in size, the microresonators were built using the Colorado Shared Instrumentation in Nanofabrication and Characterization (COSINC) clean room’s new electron beam lithography system.

The facility provides a highly-controlled environment required to work at the microscopic scales that can lead to reliable device performance.

Optical waveguide microresonators on a chip created in this effort, which are ten times thinner than human hair.

Many optical and photonic devices are smaller than the width of a piece of paper, meaning even tiny dust particles or surface imperfections can disrupt how light travels through a material.

“Traditional lithography uses photons and is fundamentally limited by the wavelength of light,” Lu said. “However, electron beam lithography has no such constraint. With electrons, we can realize our structures with sub-nanometer resolution, which is critical for our microresonators.”

For Lu, the hands-on fabrication process was a fulfilling aspect of the project.

“Clean rooms are just cool and you’re working with these massive, precise machines and then you get to see images of structures you made only microns wide. Turning a thin film of glass into a working optical circuit is really satisfying.”

A key success from the work was the ability of the researchers to use chalcogenides, a broad term encompassing a family of specialized semiconductor glasses.

“These chalcogenides are excellent materials for photonics because of their high transparency and nonlinearity,” said Park. “Our work represents one of the best performing devices using chalcogenides, if not the best.”

Chalcogenides were helpful since they have strong transparency for light to pass through the device at high intensities needed for microresonators.

However, the materials are not easy to process for the device, so there’s a balancing act to tread.

“Chalcogenides are difficult, but rewarding materials to operate for photonic nonlinear devices,” said Professor Juilet Gopinath, who has worked on this project with Park for more than ten years. “Our results showed that minimizing the bend loss enables ultra-low loss devices comparable to state-of-the-art in other materials platforms.”

Measuring light at the microscale

Erikson with the optical setup for capturing data measuring absorption and thermal effects.

Once fabricated, the microresonators were handed off for testing, work led by James Erikson, a physics PhD student specializing in laser-based measurements. He carefully aligned lasers with microscopic waveguides, coupling light into and out of the device while monitoring how it behaved inside.

They looked for ‘dips’ within the data in transmitted light that indicate resonance as photons get trapped. By analyzing the shape of those dips, they were able to extract properties like absorption and thermal effects.

“The most obvious indicator of device quality is the shape of the resonances and we want them to be deep and narrow, like a needle piercing through the signal background,” said Erikson. “We’ve been chasing this kind of resonator for a long time, and when we saw the sharp resonances on this new device we knew right away that we’d finally cracked the code.”

Erikson added, to make a good device you need to know how much light will be absorbed versus transmitted. Thermal effects become important when adding laser power as you run the risk of damaging the device.

“The way most materials interact with light also changes depending on the temperature of the material,” said Erikson, “so as a device heats up its properties can change and cause it to work differently.”

In the future, the microresonators could be used for compact microlasers, advanced chemical and biological sensors and even tools for quantum metrology and networking.

“Many photonic components from lasers, modulators and detectors are being developed and microresonators like ours will help tie all of those pieces together,” said Lu. “Eventually, the goal is to build something you could hand to a manufacturer and create hundreds of thousands of them.”

CU �鶹ӰԺ researchers have built high performing optical microresonators opening the door for new sensor technologies. In the future, the microresonators could be used for compact microlasers, advanced chemical and biological sensors and even tools for quantum metrology and networking.

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The fabrication cleanroom facility provides state-of-the-art instrumentation including lithography, thin-film deposition and among others. (Credit: COSINC)

Exploring Colorado’s untapped geothermal energy potential

Charles Ferrer — Tue, 21 Oct 2025 15:49:22 +0000

Exploring Colorado’s untapped geothermal energy potential Charles Ferrer Tue, 10/21/2025 - 09:49

Charles Ferrer

Professor Bri-Mathias Hodge

A major question looms over Colorado’s energy future: why does geothermal energy — a natural renewable resource — remain virtually untapped?

Professor Bri-Mathias Hodge, based in the Department of Electrical, Computer & Energy Engineering, along with Assistant Teaching Professor Shae Frydenlund from the Center for Asian Studies, will examine the technological and social barriers that have held back geothermal development in Colorado.

Geothermal energy comes from the natural heat stored beneath the Earth’s surface. It’s harnessed by tapping underground reservoirs of steam or hot water to produce electricity or provide direct heating.

Colorado is home to significant geothermal areas including the areas of Mount Princeton Hot Springs, Waunita Hot Springs and the San Luis Valley — yet no geothermal power plants currently operate in the state. That could soon change, thanks to growing collaboration among researchers, energy companies and policymakers.

“We know there is an abundant amount of geothermal energy potential in our state,” said Hodge, who brings two decades of experience in renewable energy integration and power systems simulation. “What we need is a better understanding of the social, economic and regulatory factors that influence its development.”

Bridging technology and community

Assistant Teaching Professor Shae Frydenlund

Frydenlund’s work with Indigenous communities in Indonesia, some of whom oppose geothermal projects due to environmental justice concerns, sparked an interdisciplinary collaboration with Hodge.

“I became very interested in bringing together physical science and social science perspectives,” Frydenlund said, “and to understand why a place as geothermal-rich as Colorado hasn’t tapped into this natural resource.”

Her research, together with Geography Professor Emily Yeh, revealed that struggles over geothermal projects emerge in and through the politics of indigeneity, land tenure and uneven development.

“There are concerns over land rights, sacred territories, livelihoods and environmental justice,” she said. “We need to bring those perspectives as we think about using geothermal here.”

To capture both the human and technical sides of geothermal development, the CU �鶹ӰԺ team will combine tools, such as power systems modeling, spatial statistics and GIS mapping along with community forums, surveys and interviews. Gaining community input will be integral for this project.

One of their main goals is to create an interactive map tool of Colorado showing potential geothermal sites, layered with data on social and technological factors.

“Just because an area has strong potential doesn’t mean it’s a good place to develop geothermal energy,” Frydenlund said. “If it’s not culturally appropriate or desired by the community, resources can be wasted and projects can fail.”

The issue isn't unique to Colorado.

“We’ve seen this already in the U.S.," Hodge said. "Hawaii has been a leader in decarbonization goals and has great geothermal resources. Yet, there’s very little being developed there because you have to be mindful of the traditions in Hawaiian culture.”

The planning phase for the project includes three major steps: campus-wide town halls to connect with geothermal experts, identifying industry and community partners across the state and gathering preliminary data through stakeholder engagement. Between January and March 2026, Frydenlund will conduct fieldwork at six sites across Colorado, including Steamboat Springs, Buena Vista and Sterling Ranch in the South Metro area.

Building toward carbon neutrality

Geothermal exploration speaks directly to CU �鶹ӰԺ’s goal of carbon neutrality by 2050 and the Western Governors Association’s Heat Beneath Our Feet initiative, which announced $7.7 million in funding in May 2024 to advance geothermal technology in Colorado.

Geothermal technologies can operate at multiple scales from single buildings to community thermal networks to large-scale power generation.

“What’s really interesting from a power systems standpoint is that geothermal affects not only electricity supply, but also demand,” Hodge said. “If ground-source heat pumps became widespread, Colorado’s power grid could shift from a summer to a winter peak system.”

However, these technological advances alone can’t drive an increased transition to geothermal.

“Understanding the intimate relationships that people have with land and with energy and with each other will make for a much richer picture of what kind of future geothermal energy has in this state,” Frydenlund said.

The project is funded by a Research & Innovation Office New Frontiers Grant.

A major question looms over Colorado’s energy future: why does geothermal energy, a renewable resource, remain virtually untapped? CU �鶹ӰԺ researchers will examine the technological and social barriers that have held back geothermal development in the state.

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Geothermal power station (Credit: Adobe)

New open-source software allows for efficient 3D printing with multiple materials

Charles Ferrer — Tue, 14 Oct 2025 14:46:52 +0000

New open-source software allows for efficient 3D printing with multiple materials Charles Ferrer Tue, 10/14/2025 - 08:46

Researchers have created an open-source design system software package that uses functions and code to map not just shapes, but where different materials belong in a 3D object. The project, called OpenVCAD, has the potential to transform 3D printing by enabling engineers to design multi-material objects smarter and more efficiently.

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Teams compete for CU �鶹ӰԺ's 2025 Lab Venture Challenge

Charles Ferrer — Tue, 30 Sep 2025 21:13:07 +0000

Teams compete for CU �鶹ӰԺ's 2025 Lab Venture Challenge Charles Ferrer Tue, 09/30/2025 - 15:13

Researchers from the Electrical, Computer & Energy Engineering Department will compete for CU �鶹ӰԺ's 2025 Lab Venture Challenge. LVC supports projects that address a commercial need, have a clear path to a compelling market and have strong scientific support.

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14er science: Quantum physicists measure whether time moves faster on a mountaintop

Charles Ferrer — Wed, 24 Sep 2025 15:47:30 +0000

14er science: Quantum physicists measure whether time moves faster on a mountaintop Charles Ferrer Wed, 09/24/2025 - 09:47

Researchers from CU �鶹ӰԺ are tackling one of the biggest challenges in quantum today: after years of scientific advancement, can we take quantum technology out of the lab and into the real and unforgiving world?

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Power electronics researchers awarded $1.5M to advance energy technologies

Charles Ferrer — Thu, 11 Sep 2025 19:37:50 +0000

Power electronics researchers awarded $1.5M to advance energy technologies Charles Ferrer Thu, 09/11/2025 - 13:37

Charles Ferrer

Luca Corradini

Imagine a future where electric vehicle charging stations or AI data center power supply systems can be built like LEGO bricks — small, stackable units that can expand as demand grows.

Luca Corradini, associate professor in the Department of Electrical, Computer and Energy Engineering, is embarking on such a project at the �鶹ӰԺ, thanks to a $1.5 million award from the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E).

“This research serves as an excellent example of the crucial importance and versatility of power electronics in today’s rapidly evolving energy technology landscape,” said Corradini. “With these innovations, industries could adopt new energy conversion solutions while making power grids more resilient, flexible and affordable.”

At its core, the project will design a Universal AC-DC Electrical Power Mover (UPM) to convert electricity from one form to another — alternating current (AC), which powers our homes and businesses, into direct current (DC), the type needed for things like fast EV charging, storing energy from solar panels or powering large AI data centers. Unlike today’s technologies, the UPM is both modular and versatile.

“We’re designing the UPM as a compact ‘brick’ that can connect directly to other identical bricks just like LEGOs,” Corradini said, who is also a faculty member at the Colorado Power Electronics Center (CoPEC). “Companies can start small and scale up their systems as needed, without a complete redesign.”

This stackable design not only simplifies installation but also allows systems to connect seamlessly to different kinds of power grids, whether lower voltage single-phase systems used in homes, or three-phase power utilized on long-distance high tension lines. Flexibility across electric grids is especially important in the United States since grid connections vary widely across regions.

Traditional power transformers, essential devices that convert voltage levels for safe and efficient electricity use, have been around for more than a century. More modern solid-state transformers are beginning to replace them, but they remain limited in their versatility and scalability.

Corradini, along with Distinguished Professor Dragan Maksimovic who is collaborating on the project, is working to break through those barriers. The UPM’s modularity and reconfigurable design could reduce costs across design, manufacturing, deployment and maintenance stages, while also opening new possibilities for energy systems.

Promising applications include EV fast charging stations, which today require costly, large-scale infrastructure, as well as large AI data centers, whose tremendous growth in electricity demand calls for scalable power solutions.

The system’s bi-directional capability also means energy could flow both ways: from the grid to vehicles or from sources like solar panels back into the grid. That could prove especially valuable in rural or poorly served areas, where additional energy support is needed.

In partnership with the National Laboratory of the Rockies, the researchers and graduate students will leverage the ARPA-E funding for extensive prototyping, lab equipment and technology-to-market efforts, including patent development and industry outreach.

Luca Corradini, associate professor in the Department of Electrical, Computer and Energy Engineering, is advancing energy technologies at CU �鶹ӰԺ thanks to a $1.5 million award from the U.S. Department of Energy’s Advanced Research Projects Agency-Energy.

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Researchers test the trustworthiness of AI—by playing sudoku

Charles Ferrer — Tue, 29 Jul 2025 16:07:05 +0000

Researchers test the trustworthiness of AI—by playing sudoku Charles Ferrer Tue, 07/29/2025 - 10:07

A team of computer scientists and study co-author Fabio Somenzi, professor in the Department of Electrical, Computer and Energy Engineering discovered that some AI large language models can solve sudoku puzzles, but even the best ones struggle to explain how they did it.

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Draper Scholar to explore 3D-printed lens design

Charles Ferrer — Tue, 01 Jul 2025 19:47:59 +0000

Draper Scholar to explore 3D-printed lens design Charles Ferrer Tue, 07/01/2025 - 13:47

Charles Ferrer

Samuel Silberman, an incoming PhD student in electrical engineering, has been named a 2025 Draper Scholar by Draper. The prestigious graduate fellowship will support his research into radio frequency (RF) lens design using advanced 3D printing and additive manufacturing.

“My Draper fellowship will focus on developing synthesis and optimization methods for the design of RF lenses,” Silberman said. “These lenses will leverage multi-material additive manufacturing and corresponding material parameters achievable through advanced 3D printing techniques.”

RF lenses are critical components in communication and radar systems, often used to create highly directional lens antennas. Through his fellowship, Silberman hopes to take advantage of innovative 3D printing capabilities to improve the performance of these devices.

The Draper Scholar Program provides five years of funding and offers scholars access to scientists and engineers at Draper in Cambridge, Massachusetts. In addition to virtual mentorship, he will travel to Draper annually to present his research and connect with other fellows across the country.

Last summer, Silberman participated in undergraduate research through Canada’s Natural Sciences and Engineering Research Council program. He worked on a resonant capacitive power transfer system for electrified roadways, conducting electromagnetic analysis and designing power electronics for the system. That hands-on experience cemented his interest in RF systems and power transfer and ultimately influenced his decision to pursue his PhD at CU �鶹ӰԺ.

“I was drawn to the work being done in electromagnetic metamaterials by my advisor, Cody Scarborough,” Silberman said, “and Colorado’s great skiing and hiking scene was an added bonus.”

He will be co-advised by Rob MacCurdy, assistant professor of mechanical engineering, on the mechanical aspects of the project.

Silberman earned his bachelor’s degree in electrical and computer engineering from the University of New Brunswick in Fredericton, Canada.

“I’m really excited to contribute to the field and grow as a researcher through this opportunity,” he said.

Samuel Silberman, an incoming PhD student in electrical engineering, has been named a 2025 Draper Scholar by Draper. The prestigious graduate fellowship will support his research into radio frequency lens design using advanced 3D printing and additive manufacturing.

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